Finding software vulnerabilities in concurrent programs is a challenging task due to the size of the state-space exploration, as the number of interleavings grows exponentially with the number of program threads and statements. We propose and evaluate EBF (Ensembles of Bounded Model Checking with Fuzzing) - a technique that combines Bounded Model Checking (BMC) and Gray-Box Fuzzing (GBF) to find software vulnerabilities in concurrent programs. Since there are no publicly-available GBF tools for concurrent code, we first propose OpenGBF - a new open-source concurrency-aware gray-box fuzzer that explores different thread schedules by instrumenting the code under test with random delays. Then, we build an ensemble of a BMC tool and OpenGBF in the following way. On the one hand, when the BMC tool in the ensemble returns a counterexample, we use it as a seed for OpenGBF , thus increasing the likelihood of executing paths guarded by complex mathematical expressions. On the other hand, we aggregate the outcomes of the BMC and GBF tools in the ensemble using a decision matrix, thus improving the accuracy of EBF . We evaluate EBF against state-of-the-art pure BMC tools and show that it can generate up to 14.9% more correct verification witnesses than the corresponding BMC tools alone. Furthermore, we demonstrate the efficacy of OpenGBF , by showing that it can find 24.2% of the vulnerabilities in our evaluation suite, while non-concurrency-aware GBF tools can only find 0.55%. Finally, thanks to our concurrency-aware OpenGBF , EBF detects a data race in the open-source wolfMqtt library and reproduces known bugs in several other real-world programs, which demonstrates its effectiveness in finding vulnerabilities in real-world software.